The Six Care Management Challenges Healthcare Must Overcome

To succeed in ambulatory care management, healthcare organizations must do three things:

Successfully acquire and consolidate information from a variety of sources and formats— EMRs, claims, authorization and other payer lists, and, potentially, third party risk vendors—all with their own unique and disparate ways of identifying patients and creating a coherent picture of patients’ care management needs.

Stratify patients and align them with the needed level of services—no more—to enable them to achieve outcomes while minimizing costs.

The Current State of Care Management: A Frustrating Workflow

Here’s what typically happens in a typical care management workflow: a long-suffering data analyst (or small team of analysts) consolidates multiple payer lists and targeted reports into one master spreadsheet, reconciles duplicates, performs Excel wizardry to reconcile formatting differences, matches the patient to an EMR or creates an EMR, and then emails patient list spreadsheets to care managers. After the patients are added (or declined) to the program, the data analyst must then manage the process of recording each patient’s care management status back to the payer and capturing the activities needed to monitor and report on program performance.

There are many consequences of this common yet problematic care management workflow:

Causes confusion (multiple emails and multiple staff reaching out to the patient—each representing a program-centric, not patient-centric, approach).

Prevents/delays the development of additional care management programs and patient populations.

Six Care Management Challenges to Overcome

To achieve the Triple Aim, organizations must improve the tools and processes used to impact care. Let’s dive into six care management challenges the industry must overcome.

#1: Fragmentation

Figure 1 demonstrates the fragmented, manual processes in a typical care management workflow. Care management is a patient-centric, longitudinal ambulatory activity that must see more than just claims and EMR data. More importantly, the view of the healthcare data needs to transcend programs and become patient centric so that one care management team can see and address patient needs holistically. Each source tells an important chapter of the bigger care management story—a story that individual sources alone can’t tell. Taking a patient-centric vs. program-centric approach avoids care teams providing contradicting advice and improves the patient experience.

Figure 1: Care Management Workflow (Current)

#2: Limited Data Access

Acquiring data for care delivered outside of the risk-bearing entity is critical to analyzing the patient situation and formulating an effective plan. Yet many healthcare organizations do not have experience negotiating and collaborating with insurers for complete patient data. The legacy of outsourcing further complicates the discussion—are they getting medical claims? Dispensed medications? Behavioral health? Are there any state laws or payer policies that limit patient-specific data provided?

Payers may be concerned that healthcare organizations will use the data provided under the guise of care management to analyze discounts and negotiate more favorable payment rates. Navigating these waters to obtain needed data is unfamiliar territory. Shifting from spreadsheets, emails, and EMR reports to a direct, standard data feed that is consistent across payers to support automation is a significant challenge.

#3: Poor Data Quality

Each source has its own method to uniquely identify patients. Social security numbers are rarely provided or are truncated and, so far, there isn’t a universal identifier for a patient. The result is that organizations also need to learn about and implement Enterprise Master Patient Index (EMPI) approaches to unify all the unique identifiers and their disparate data into a single record for each person. But leveraging EMPIs will require significant collaboration between care management and the healthcare organizations information technology departments.

Manual operational processes lead to inefficiency that diverts care managers from important patient care activities, and results in gaps in information needed to evaluate program impact and answer several questions:

How fast are we engaging patients when a need is identified?

How are we doing engaging patients?

Are we impacting healthcare utilization?

What are our local best practices?

#4: Limited Involvement in IT and Data Governance

Because of the manual nature of care management work, care management leadership may not be involved in data governance and road mapping. Care management needs to build new or strengthen relationships with Accountable Care teams, IT, and Business Intelligence teams, and provide compelling reasons to add their needs to already full project lists and road maps.

Without data governance involvement, care management teams don’t have a mechanism for communicating and prioritizing data quality issues, needs, or participating in system-wide initiatives that impact them, such as EMPI or Enterprise Data Warehouse (EDW) projects. As care management teams embrace automation, they will rely on effective IT and data governance to express concerns, develop strategic relationships, and get their needs incorporated into strategic and IT plans.

#5: Lack of Standardization

There are limited best practices in ambulatory care management. It is common to hire experienced staff and rely solely on their discretion which leads to highly variable results. There are limited standards in care management—workflows, assessments, care plans, care coordination, patient engagement approaches, definitions, etc. Achieving a standard care management workflow also requires honing technical skills in current state flow analysis and mapping—skills that are in high demand and short supply. It also requires resources who have both the clinical and operational context and an understanding of IT to balance the needs and limitations of both. Only a very small subset of staff has the knowledge, skills, and aptitude to perform these analyses and excel in process improvement work. Systems must identify these staff, support them, and provide the leadership to drive needed changes.

#6: Limited Visibility and Transparency for Program Evaluation

Health systems need access to analytics to determine what’s working and what’s not. Leadership needs to track how changes made impact program performance spanning patient identification, enrollment, assessment, management and collaboration. They need to monitor key operational metrics, identify local best practices, and report on the results the care team is achieving.

The Future of Care Management: Streamlined, Automated, and Patient Centric

Experiencing these six common care management challenges isn’t an indication of poor quality—it’s a symptom of an immature market lacking the right technology to manage in a patient-centric, not healthcare-centric, model. But implementing the right technology is only 20 percent of the solution—the other 80 percent requires rethinking use of people and processes. Changing processes and people relies on adaptive leadership and change management skills.

Overcoming these six care management challenges, though difficult, is a critical part of the industry-wide effort to deliver high quality care at a much lower cost. Fortunately, a new approach to care management is on the horizon—one that streamlines and speeds the throughput of new patients for care management; one that puts an end to the unsustainable, manual heroics of data analysts and care managers, freeing them up to add patients and programs that better serve their markets. The future of care management is streamlined, automated, and puts patients—not health systems—at the center of the healthcare universe.